1. |
|
|
2. |
|
|
3. |
- Guha, Rajarshi, et al.
(author)
-
Collaborative Cheminformatics Applications
- 2011
-
In: Collaborative Computational Technologies for Biomedical Research. - Hoboken, N.J. : John Wiley & Sons. - 9780470638033
-
Book chapter (other academic/artistic)
|
|
4. |
- Hastings, Janna, et al.
(author)
-
The Chemical Information Ontology : provenance and disambiguation for chemical data on the biological Semantic Web
- 2011
-
In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:10, s. e25513-
-
Journal article (peer-reviewed)abstract
- Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project.
|
|
5. |
- Kuhn, Thomas, et al.
(author)
-
CDK-Taverna : an open workflow environment for cheminformatics
- 2010
-
In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11, s. 159-
-
Journal article (peer-reviewed)abstract
- Background Small molecules are of increasing interest for bioinformatics in areas such as metabolomics and drug discovery. The recent release of large open access chemistry databases generates a demand for flexible tools to process them and discover new knowledge. To freely support open science based on these data resources, it is desirable for the processing tools to be open-source and available for everyone. Results Here we describe a novel combination of the workflow engine Taverna and the cheminformatics library Chemistry Development Kit (CDK) resulting in a open source workflow solution for cheminformatics. We have implemented more than 160 different workers to handle specific cheminformatics tasks. We describe the applications of CDK-Taverna in various usage scenarios. Conclusions The combination of the workflow engine Taverna and the Chemistry Development Kit provides the first open source cheminformatics workflow solution for the biosciences. With the Taverna-community working towards a more powerful workflow engine and a more user-friendly user interface, CDK-Taverna has the potential to become a free alternative to existing proprietary workflow tools.
|
|
6. |
- O'Boyle, Noel, et al.
(author)
-
Open Data, Open Source and Open Standards in chemistry : The Blue Obelisk five years on
- 2011
-
In: Journal of Cheminformatics. - : BioMed Central. - 1758-2946. ; 3, s. 37-
-
Journal article (peer-reviewed)abstract
- Background: The Blue Obelisk movement was established in 2005 as a response to the lack of Open Data,Open Standards and Open Source (ODOSOS) in chemistry. It aims to make it easier to carry out chemistryresearch by promoting interoperability between chemistry software, encouraging cooperation between OpenSource developers, and developing community resources and Open Standards. Results: This contribution looks back on the work carried out by the Blue Obelisk in the past 5 years and surveysprogress and remaining challenges in the areas of Open Data, Open Standards, and Open Source in chemistry. Conclusions: We show that the Blue Obelisk has been very successful in bringing together researchers anddevelopers with common interests in ODOSOS, leading to development of many useful resources freely availableto the chemistry community
|
|
7. |
- Samwald, Matthias, et al.
(author)
-
Linked open drug data for pharmaceutical research and development
- 2011
-
In: Journal of Cheminformatics. - : Springer Science and Business Media LLC. - 1758-2946. ; 3, s. 19-
-
Journal article (peer-reviewed)abstract
- There is an abundance of information about drugs available on the Web. Data sources range from medicinal chemistry results, over the impact of drugs on gene expression, to the outcomes of drugs in clinical trials. These data are typically not connected together, which reduces the ease with which insights can be gained. Linking Open Drug Data (LODD) is a task force within the World Wide Web Consortium's (W3C) Health Care and Life Sciences Interest Group (HCLS IG). LODD has surveyed publicly available data about drugs, created Linked Data representations of the data sets, and identified interesting scientific and business questions that can be answered once the data sets are connected. The task force provides recommendations for the best practices of exposing data in a Linked Data representation. In this paper, we present past and ongoing work of LODD and discuss the growing importance of Linked Data as a foundation for pharmaceutical R&D data sharing.
|
|
8. |
- Spjuth, Ola, 1977-, et al.
(author)
-
A novel infrastructure for chemical safety predictions with focus on human health
- 2012
-
In: Toxicology Letters. - : Elsevier BV. - 0378-4274 .- 1879-3169. ; 211:Supplm, s. S59-
-
Journal article (peer-reviewed)abstract
- A major objective of Computational Toxicology is to provide reliable and useful estimates in silico of (potentially) harmful actions of chemicals in humans. Predictive models are commonly based on in vitro and in vivo data, and aims at supporting risk assessment in various areas, including the environmental protection, food, and pharmaceutical sectors. The field is however hampered by the lack of standards, access to high quality data, validated predictive models, as well as means to connect toxicity data to genomics data.We present a framework and roadmap for a novel public infrastructure for predictive computational toxicology and chemical safety assessment, consisting of: (1) a repository capable of aggregating high quality toxicity data with gene expression data, (2) a repository where scientists can share and download predictive models for chemical safety, and (3) a user-friendly platform which makes the services and resources accessible for the scientific community. Databases under the framework will adhere to open standards and use standardized open exchange formats in order to interoperate with emerging international initiatives, such as the FP7-funded OpenTox and ToxBank projects.The infrastructure will strengthen and facilitate already ongoing activities within in silico toxicology, open up new possibilities for incorporating genomics data in chemicals safety modeling (toxicogenomics), as well as deepen the exploitation of signal transduction networks. The initiative will lay the foundation needed to boost decision support in risk assessment in a wide range of fields, including drug discovery, food safety, as well as agricultural and ecological safety assessment.
|
|
9. |
- Spjuth, Ola, 1977-, et al.
(author)
-
Applications of the InChI in cheminformatics with the CDK and Bioclipse
- 2013
-
In: Journal of Cheminformatics. - : Springer Science and Business Media LLC. - 1758-2946. ; 5:14
-
Journal article (peer-reviewed)abstract
- BackgroundThe InChI algorithms are written in C++ and not available as Java library. Integration into softwarewritten in Java therefore requires a bridge between C and Java libraries, provided by the Java NativeInterface (JNI) technology.ResultsWe here describe how the InChI library is used in the Bioclipse workbench and the Chemistry Development Kit (CDK) cheminformatics library. To make this possible, a JNI bridge to the InChIlibrary was developed, JNI-InChI, allowing Java software to access the InChI algorithms. By usingthis bridge, the CDK project packages the InChI binaries in a module and offers easy access fromJava using the CDK API. The Bioclipse project packages and offers InChI as a dynamic OSGi bundlethat can easily be used by any OSGi-compliant software, in addition to the regular Java Archive andMaven bundles. Bioclipse itself uses the InChI as a key component and calculates it on the fly whenvisualizing and editing chemical structures. We demonstrate the utility of InChI with various applications in CDK and Bioclipse, such as decision support for chemical liability assessment, tautomergeneration, and for knowledge aggregation using a linked data approach.ConclusionsThese results show that the InChI library can be used in a variety of Java library dependency solutions, making the functionality easily accessible by Java software, such as in the CDK. The applications show various ways the InChI has been used in Bioclipse, to enrich its functionality.
|
|
10. |
- Spjuth, Ola, 1977-, et al.
(author)
-
Bioclipse-R : Integrating management and visualization of life science data with statistical analysis
- 2013
-
In: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 29:2, s. 286-289
-
Journal article (peer-reviewed)abstract
- Bioclipse, a graphical workbench for the life sciences, provides functionality for managing and visualizing life science data. We introduce Bioclipse-R, which integrates Bioclipse and the statistical programming language R. The synergy between Bioclipse and R is demonstrated by the construction of a decision support system for anticancer drug screening and mutagenicity prediction, which shows how Bioclipse-R can be used to perform complex tasks from within a single software system.
|
|